Back to search
Company Description
Job Description
The Lead Data Scientist will provide visionary technical leadership to a team of data scientists and AI engineers, driving the end-to-end development and deployment of cutting-edge Artificial Intelligence solutions for our National Security clientele. This pivotal AI leadership role is instrumental in establishing a robust culture of decision-making Agentic AI and creating the AI platforms, the "brain" of Air, designed to be leveraged by a broad community of AI and Data Science professionals within Air.
As a hands-on technical leader, you will apply deep expertise in Artificial Intelligence and a keen understanding of complex Defense Acquisition challenges. Your primary focus will be to work with our proprietary and commercial datasets to find critical connections, derive actionable knowledge, and identify potential issues that help our government clients make more informed decisions. This involves designing, developing, and rapidly deploying scalable AI solutions that transform these insights into mission-critical capabilities. You will also have the opportunity to expand and grow data-driven research across Air, leading new areas to apply advanced analytics to drive strategic business and national security results. You'll apply your deep knowledge in advanced simulation and optimization techniques, including Discrete Event Simulation, Monte Carlo methods, and stochastic optimization, to enhance our platforms to handle complex capability simulation and optimization techniques for critical defense use cases.
To excel in this position, you must be an AI expert with a strong command of data science fundamentals and a proven ability to bring data-driven solutions to life within the defense ecosystem. The ideal candidate is a highly organized problem-solver who possesses excellent oral and written communication skills, capable of translating complex AI concepts for both technical and non-technical audiences. You must be independent, driven, and motivated to jump in and roll up your sleeves to get the job done. You lead by influence and motivation, demonstrating a passion for great work and an intolerance for mediocrity. We seek an uber-smart, creative, out-of-the-box thinker who is challenged by complex defense problems and obsessed with quality and rapid prototyping/deployment, knowing how to engage in constructive dialogue to find the best path forward.
This role is a full-time position located out of our office in Pittsburgh, PA.ÂThis role may require up to 10% travel
Scope of Responsibilities
- Â Drive the development of a complex, multi-modal decision intelligence system, serving as the central nervous architecture for integrating advanced simulation, optimization, and predictive modeling capabilities across Air Enterprise Readiness platform.
- Â Define the multi-year technical roadmap for AI initiatives, turning vague business challenges into concrete, scalable research and product goals.
- Raise the collective bar by mentoring Senior-level engineers and building high-performing teams that consistently deliver state-of-the-art (SOTA) results.
- Drive consensus across disparate groups such as DS and AI, Product, Forward Deployed AI and Engineering, to ensure AI deployments are technically sound, commercially viable, and responsible.
- Act as the authority on scientific breakthroughs and model strategy, ensuring that core architectures, training methodologies, and data ecosystems are robust, cost-effective, and future-proofed against the rapidly evolving AI landscape
- Lead the end-to-end execution of large-scale AI projects, ensuring alignment with strategic objectives and timely delivery.
- Apply deep knowledge in advanced simulation and optimization techniques, including Discrete Event Simulation, Monte Carlo methods, and stochastic optimization.
- Enhance our platforms to handle complex capability simulation and optimization techniques for critical defense use cases.
- Act as the primary Individual Contributor (IC) and technical lead for complex AI/ML/DS projects, taking deep ownership from ideation to production deployment.
- Serve as the domain expert in a specific area of AI (e.g., Deep Learning, Natural Language Processing, Decision Science), driving the application and development of state-of-the-art methods within that specialization.
- Work closely with partner teams, including AI research, data engineering, and software development, to define robust software architecture, set the project roadmap, and manage technical execution.
- Collaborate with the Product team to clearly define product scope, translating high-level requirements into actionable technical plans and delivering market-ready AI solutions integrated with client data platforms and workflows.
- Drive the development of scalable, AI-based platforms designed to support and power solutions for a diverse range of customers within the defense ecosystem.
- Champion the introduction of new AI innovations. Stay current with the rapidly evolving fields of Artificial Intelligence, including advanced methods in simulation and optimization, Large Language Models (LLMs), and agentic systems, and actively transfer this knowledge and best practices for implementation across the team.
- Mentor and guide junior and senior team members, fostering a culture of technical excellence, continuous learning, and high-impact work.
- Nurture a robust AI culture within the team by leading technical discussions, conducting internal workshops, and promoting best practices in model development, experimentation, and MLOps.
- Demonstrate strong leadership qualities to align the team's AI strategy effectively with overall business and client needs, translating complex technical concepts into strategic business impacts for leadership.
Qualifications
- U.S. Citizenship is required
- Minimum of 7 years of professional experience working as a Data Scientist in an industry setting
- Oversee the full lifecycle of large-scale AI projects.
- Possess deep knowledge and the ability to apply techniques such as Discrete Event Simulation (DES), agent based modeling and Monte Carlo methods to model complex capabilities.
- Deep understanding and application of advanced optimization techniques, specifically including stochastic optimization.
- Deep understanding and practical experience with Bayesian optimization, causal discovery, and causal modeling.
- Ability to leverage simulation and optimization knowledge to enhance platforms for complex capability simulation and optimization in critical defense use cases.
- Understanding of coding AI (such as Claude Code) and experience in using it to scale up AI team deliveries
- Expertise in leveraging deep technical knowledge of AI solution internals (such as Deep Research systems) to design and implement custom, highly optimized solutions.
- Ensure timely project delivery and strategic goal alignment.
- Collaborate with cross-functional teams (AI Research, Data Engineering, Software Development). Â
- Define robust software architecture for large-scale AI systems and project roadmaps.
- Translate high-level product requirements into actionable technical plans.
- Deliver production-ready AI solutions integrated with clients' data platforms and workflows.
- Drive the implementation of scalable AI/ML platforms.
- Maintain deep expertise in cutting-edge AI, including LLMs and agentic systems. Train models, build systems based on AI innovations
- Champion innovation and best practices across the organization.
- Mentor and coach team members.
- Foster a high-performing culture of technical excellence and continuous growth.
- Help to the leadership to align AI strategy effectively with client needs.
- Create agentic AI systems, using AI orchestrators and particular AI reasoning capabilities as tools.
Desired Skills:Â
- A strong publication record in the top conferences in one of the AI, ML NLP, and decision science areas
- Deep knowledge of LLM and Agentic system evaluation, experience in building evaluation systems
- Experience in LLM post-training or fine-tuningÂ
- Demonstrate strong National Security domain knowledge.
- Experience with MLOps practices, including deployment, monitoring, and management of large-scale models in cloud environments (e.g., GCP, AWS, Azure).
- Track record of successfully transitioning AI research prototypes into robust, production-grade enterprise solutions
Learn more about this Employer on their Career Site
